Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
10324189 | Fuzzy Sets and Systems | 2005 | 33 Pages |
Abstract
This paper presents a hybrid neural network, called the self-organising fuzzy neural network (SOFNN), to extract fuzzy rules from the training data. The first hidden layer of this network consists of ellipsoidal basis function (EBF) neurons. Every EBF neuron in the SOFNN has both a centre vector and a width vector. Neurons are organised by the network itself. The methods of the structure and parameter learning, based on new adding and pruning techniques and a recursive learning algorithm, are simple and effective, with a high accuracy and a compact structure. Simulations show that the SOFNN has the capability to encode fuzzy rules in the resulting network.
Keywords
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Gang Leng, Thomas Martin McGinnity, Girijesh Prasad,